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Found 388 Skills
Prometheus monitoring and alerting for cloud-native observability. USE WHEN: Writing PromQL queries, configuring Prometheus scrape targets, creating alerting rules, setting up recording rules, instrumenting applications with Prometheus metrics, configuring service discovery. DO NOT USE: For building dashboards (use /grafana), for log analysis (use /logging-observability), for general observability architecture (use senior-software-engineer with infrastructure focus). TRIGGERS: metrics, prometheus, promql, counter, gauge, histogram, summary, alert, alertmanager, alerting rule, recording rule, scrape, target, label, service discovery, relabeling, exporter, instrumentation, slo, error budget.
Use when working with AWS Strands Agents SDK or Amazon Bedrock AgentCore platform for building AI agents. Provides architecture guidance, implementation patterns, deployment strategies, observability, quality evaluations, multi-agent orchestration, and MCP server integration.
Principal backend engineering intelligence for Python AI/ML systems. Actions: plan, design, build, implement, review, fix, optimize, refactor, debug, secure, scale ML services and pipelines. Focus: data quality, reproducibility, reliability, performance, security, observability, model evaluation, MLOps.
Azure Application Insights SDK for .NET. Application performance monitoring and observability resource management. Use for creating Application Insights components, web tests, workbooks, analytics items, and API keys. Triggers: "Application Insights", "ApplicationInsights", "App Insights", "APM", "application monitoring", "web tests", "availability tests", "workbooks".
Create Post Incident Records (PIRs) by analysing incidents discovered from PagerDuty. Orchestrates pagerduty-oncall, datadog-analyser, and traffic-spikes-investigator skills to enrich each incident with observability and traffic data, auto-determines severity, and outputs completed PIR forms. Use when asked to "create a PIR", "write a post incident record", "fill out PIR form", "incident report", "analyse incidents", or after on-call shifts need documentation.
Lead complex software implementation, architecture decisions, and reliable delivery across any modern technology stack. Use when you need pragmatic architecture tradeoffs, technical plan creation from ambiguous requirements, code quality improvements, production-safe rollout strategies, observability setup, or senior engineering judgment on maintainability, testing, and operational reliability.
Use this skill when implementing data validation, data quality monitoring, data lineage tracking, data contracts, or Great Expectations test suites. Triggers on schema validation, data profiling, freshness checks, row-count anomalies, column drift, expectation suites, contract testing between producers and consumers, lineage graphs, data observability, and any task requiring data integrity enforcement across pipelines.
Use this skill when working with PostHog - product analytics, web analytics, feature flags, A/B testing, experiments, session replay, error tracking, surveys, LLM observability, or data warehouse. Triggers on any PostHog-related task including capturing events, identifying users, evaluating feature flags, creating experiments, setting up surveys, tracking errors, and querying analytics data via the PostHog API or SDKs (posthog-js, posthog-node, posthog-python).
Spring Modulith for modular architecture in Spring Boot 3.x. Covers module structure, API vs internal packages, inter-module events, module testing, documentation generation, and observability. USE WHEN: user mentions "spring modulith", "modular monolith", "@ApplicationModule", "module boundaries", "inter-module events", "@ApplicationModuleTest", "modular architecture" DO NOT USE FOR: simple applications - unnecessary complexity, microservices - use proper service boundaries, existing tightly coupled monoliths - requires significant refactoring
Salesforce Data Cloud Retrieve phase. TRIGGER when: user runs Data Cloud SQL, describe, async queries, vector search, search-index workflows, or metadata introspection for Data Cloud objects. DO NOT TRIGGER when: the task is standard CRM SOQL (use sf-soql), segment creation or calculated insight design (use sf-datacloud-segment), or STDM/session tracing/parquet analysis (use sf-ai-agentforce-observability).
Salesforce Data Cloud Harmonize phase. TRIGGER when: user works with DMOs, mappings, relationships, identity resolution, unified profiles, data graphs, or universal IDs. DO NOT TRIGGER when: the task is only about streams/DLOs (use sf-datacloud-prepare), segments/insights (use sf-datacloud-segment), retrieval/search (use sf-datacloud-retrieve), or STDM/session tracing (use sf-ai-agentforce-observability).
Salesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase `sf data360` workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching sf-datacloud-* skill), the task is STDM/session tracing/parquet telemetry (use sf-ai-agentforce-observability), standard CRM SOQL (use sf-soql), or Apex implementation (use sf-apex).